Sepsis is a major health problem in high-risk newborn infants in the neonatal intensive care unit (NICU), where it occurs in 25 percent of very low birth weight infants and leads to a more than doubling of mortality and a 50 percent increase in hospital stay. Our long-term objective is to test the hypothesis that detection of abnormal heart rate characteristics (HRC) with continuous non-invasive monitoring will improve care of these patients by earlier diagnosis of sepsis and other sub-acute, potentially catastrophic illnesses. We propose to advance toward this objective by completing two research aims. In Aim 1, we will prospectively study unselected infants in a university NICU to test the hypotheses that abnormal HRC will be associated with upcoming sepsis and sepsis-like illness as defined by objective illness criteria, and that HRC adds significant independent diagnostic information about the risk of sepsis and sepsis-like illness to clinical variables of birth weight and gestational age. The clinical research design is for derivation of multivariable predictive statistical models from one set of patients followed by a validation phase using clinical data from a second set of patients. In Aim 2, we will develop new measures of HRC that are specific to the task of early detection of neonatal sepsis. We will investigate optimum choice of parameters for sample entropy calculation, stationarity of heart rate time series using conventional and novel measures based on the empirical cumulative distribution function, and frequency domain analysis using a novel method.